Skip to main content

An Automata-Based Microscopic Model Inspired by Clonal Expansion

  • Chapter
Mathematical Modeling of Biological Systems, Volume II

Summary

We present a simple model based on microscopic automata to describe the clonal expansion process. The model is based on a repertoire of antigens and T lymphocytes interacting via antigen-presenting cells which present the antigens peptides. Each cell is represented by an automaton moving randomly on a two-dimensional lattice.We use this simplified model in order to introduce local and spatial considerations in the mathematical models of clonal expansion based on differential equations, and at the same time to attempt an analytical interpretation of the results of computer simulations. For this reason we also derive a mean field theory, whose results are in good agreement with the solutions of the microscopic model, at least for situations that are not too far from equilibrium. This model may be used as the basis of a more realistic one that could follow the clonal expansion process on a simplified version of the lymphatic network.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. De Boer, R., Perelson, A.S.: T cells repertoires and competitive exclusion. J. Theor. Biol., 169, 375–390 (1994).

    Article  Google Scholar 

  2. Hofbauer, J., Sigmund, K.: Evolutionary Games and Population Dynamics. Cambridge University Press, London (1998).

    MATH  Google Scholar 

  3. Novak, M., May, R., Sigmund, K.: Immune responses against multiple epitopes. J. Theor. Biol., 175, 325–350 (1994).

    Google Scholar 

  4. Antia, R., Ganusov, V., Ahmed, R.: The role of models in understanding CD8+ T-cell memory. Nature Reviews Immunology (published online 20 January 2005).

    Google Scholar 

  5. De Boer, R., Perelson, A.S.: Competitive control of the self renewing T cell repertoire. International Immunology, Vol. 9, No. 5, p. 779, Oxford University Press, London (1997).

    Google Scholar 

  6. Lanzavecchia, A., Sallustio, F.: Lead and follow: the dance of the dentritic cell and T cell. Nature Immunology, 5, 1201–1202 (2004).

    Article  Google Scholar 

  7. Hugues, S., Fetler, L., Bonifaz, L., Helft, J., Amblard, F., Amigorena, S.: Distinct T cell dynamics in lymph nodes during the induction of tolerance and immunity. Nature Immunology, 5, 1235–1242 (2004).

    Article  Google Scholar 

  8. Lindquist, R., Shakhar, G., Dudziak, D., Wardemann, H., Eisenreich, T., Dustin, M., Nussenzweig, M.: Visualizing dendritic cell networks in vivo. Nature Immunology, 5, 1243–1247 (2004).

    Article  Google Scholar 

  9. Germain, R., Jenkins, M.: In vivo antigen presentation. Current Opinion in Immunology, 16, 120–125.

    Google Scholar 

  10. Callard, R., Stark, J., Yates, A.: Fratricide: a mechanism for T memory-cell homeostasis. Trends in Immunology, 24, 370–375 (2003).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Birkhäuser Boston

About this chapter

Cite this chapter

Zanlungo, F., Rambaldi, S., Turchetti, G. (2008). An Automata-Based Microscopic Model Inspired by Clonal Expansion. In: Deutsch, A., et al. Mathematical Modeling of Biological Systems, Volume II. Modeling and Simulation in Science, Engineering and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4556-4_12

Download citation

Publish with us

Policies and ethics